Machine Learning Engineer I

Handshake Handshake · Enterprise · San Francisco, CA · Engineering

This Machine Learning Engineer role focuses on developing and deploying ML models that directly impact user experience and business metrics for a consumer platform. The role involves end-to-end ownership of the ML lifecycle, working with cutting-edge infrastructure like embedding-based retrieval and multi-stage rankers, and contributing to responsible AI practices.

What you'd actually do

  1. Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization — with guidance from senior engineers.
  2. Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.
  3. Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.

Skills

Required

  • Python
  • scikit-learn
  • PyTorch
  • TensorFlow
  • classification
  • regression
  • ranking
  • model evaluation

Nice to have

  • recommendations
  • personalization
  • NLP
  • deep learning
  • LLMs
  • explainable AI
  • experiment tracking
  • model monitoring
  • feature pipelines
  • GCP
  • AWS
  • Azure
  • communicator
  • cross-functional collaboration

What the JD emphasized

  • End-to-end ownership
  • Product impact
  • Cutting-edge infrastructure
  • Scale
  • Billions of data points

Other signals

  • Machine learning is at the heart of Handshake's mission
  • Your ML systems directly impact millions of users and drive critical business metrics
  • Work with embedding-based retrieval, Graph Neural Networks, and multi-stage rankers
  • Billions of data points powering our ML systems